Neural representations of events arise from temporal community structure | Nature Neuroscience
Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Neural representations of events arise from temporal community structure

Nature Neuroscience volume 16, pages 486–492 (2013)Cite this article

Subjects

Abstract

Our experience of the world seems to divide naturally into discrete, temporally extended events, yet the mechanisms underlying the learning and identification of events are poorly understood. Research on event perception has focused on transient elevations in predictive uncertainty or surprise as the primary signal driving event segmentation. We present human behavioral and functional magnetic resonance imaging (fMRI) evidence in favor of a different account, in which event representations coalesce around clusters or 'communities' of mutually predicting stimuli. Through parsing behavior, fMRI adaptation and multivoxel pattern analysis, we demonstrate the emergence of event representations in a domain containing such community structure, but in which transition probabilities (the basis of uncertainty and surprise) are uniform. We present a computational account of how the relevant representations might arise, proposing a direct connection between event learning and the learning of semantic categories.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Design and stimuli.
Figure 2: Behavioral results.
Figure 3: Results of GLM analyses.
Figure 4: Pattern similarity results.
Figure 5: Neighboring regions found in adaptation and pattern analysis.
Figure 6: Model architecture and results.

Similar content being viewed by others

References

  1. Speer, N.K., Swallow, K.M. & Zacks, J.M. Activation of human motion processing areas during event perception. Cogn. Affect. Behav. Neurosci. 3, 335–345 (2003).

    Article  Google Scholar 

  2. Newtson, D. Attribution and the unit of perception of ongoing behavior. J. Pers. Soc. Psychol. 28, 28–38 (1973).

    Article  Google Scholar 

  3. Reynolds, J.R., Zacks, J.M. & Braver, T.S. A computational model of event segmentation from perceptual prediction. Cogn. Sci. 31, 613–643 (2007).

    Article  Google Scholar 

  4. Baldwin, D., Andersson, A., Saffran, J. & Meyer, M. Segmenting dynamic human action via statistical structure. Cognition 106, 1382–1407 (2008).

    Article  Google Scholar 

  5. Zacks, J.M., Kurby, C.A., Eisenberg, M.L. & Haroutunian, N. Prediction error associated with the perceptual segmentation of naturalistic events. J. Cogn. Neurosci. 23, 4057–4066 (2011).

    Article  Google Scholar 

  6. Avrahami, J. & Kareev, Y. The emergence of events. Cognition 53, 239–261 (1994).

    Article  CAS  Google Scholar 

  7. Saffran, J.R., Aslin, R.N. & Newport, E.L. Statistical learning by 8-month-old infants. Science 274, 1926–1928 (1996).

    Article  CAS  Google Scholar 

  8. Rosch, E. & Mervis, C.B. Family resemblances: Studies in the internal structure of categories. Cognit. Psychol. 7, 573–605 (1976).

    Article  Google Scholar 

  9. Medin, D.L. & Schaffer, M.M. Context theory of classification learning. Psychol. Rev. 85, 207–238 (1978).

    Article  Google Scholar 

  10. Rogers, T.T. & McClelland, J.L. Semantic Cognition: A Parallel Distributed Processing Approach (MIT Press, Cambridge, Massachusetts, 2004).

  11. Fortunato, S. Community detection in graphs. Phys. Rep. 486, 75–174 (2010).

    Article  Google Scholar 

  12. Newman, M.E.J. The structure and function of complex networks. SIAM Rev. 45, 167–256 (2003).

    Article  Google Scholar 

  13. Newman, M.E. Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA 103, 8577–8582 (2006).

    Article  CAS  Google Scholar 

  14. Girvan, M. & Newman, M.E. Community structure in social and biological networks. Proc. Natl. Acad. Sci. USA 99, 7821–7826 (2002).

    Article  CAS  Google Scholar 

  15. Rosvall, M. & Bergstrom, C.T. Maps of random walks on complex networks reveal community structure. Proc. Natl. Acad. Sci. USA 105, 1118–1123 (2008).

    Article  CAS  Google Scholar 

  16. Zacks, J.M. et al. Human brain activity time-locked to perceptual event boundaries. Nat. Neurosci. 4, 651–655 (2001).

    Article  CAS  Google Scholar 

  17. Turk-Browne, N.B., Scholl, B.J. & Chun, M.M. Babies and brains: habituation in infant cognition and functional neuroimaging. Front. Hum. Neurosci 2, 16 (2008).

    PubMed  PubMed Central  Google Scholar 

  18. Grill-Spector, K., Henson, R. & Martin, A. Repetition and the brain: neural models of stimulus-specific effects. Trends Cogn. Sci. 10, 14–23 (2006).

    Article  Google Scholar 

  19. Schapiro, A.C., Kustner, L.V. & Turk-Browne, N.B. Shaping of object representations in the human medial temporal lobe based on temporal regularities. Curr. Biol. 22, 1622–1627 (2012).

    Article  CAS  Google Scholar 

  20. Press, C., Weiskopf, N. & Kilner, J.M. Dissociable roles of human inferior frontal gyrus during action execution and observation. Neuroimage 60, 1671–1677 (2012).

    Article  Google Scholar 

  21. James, T.W. & Gauthier, I. Repetition-induced changes in BOLD response reflect accumulation of neural activity. Hum. Brain Mapp. 27, 37–46 (2006).

    Article  Google Scholar 

  22. Turk-Browne, N.B., Yi, D.J., Leber, A.B. & Chun, M.M. Visual quality determines the direction of neural repetition effects. Cereb. Cortex 17, 425–433 (2007).

    Article  CAS  Google Scholar 

  23. Thompson-Schill, S.L. Neuroimaging studies of semantic memory: inferring “how” from “where”. Neuropsychologia 41, 280–292 (2003).

    Article  Google Scholar 

  24. Moss, H.E. et al. Selecting among competing alternatives: selection and retrieval in the left inferior frontal gyrus. Cereb. Cortex 15, 1723–1735 (2005).

    Article  CAS  Google Scholar 

  25. Vandenberghe, R., Price, C., Wise, R., Josephs, O. & Frackowiak, R.S. Functional anatomy of a common semantic system for words and pictures. Nature 383, 254–256 (1996).

    Article  CAS  Google Scholar 

  26. Homae, F., Hashimoto, R., Nakajima, K., Miyashita, Y. & Sakai, K.L. From perception to sentence comprehension: the convergence of auditory and visual information of language in the left inferior frontal cortex. Neuroimage 16, 883–900 (2002).

    Article  Google Scholar 

  27. Ueno, T., Saito, S., Rogers, T.T. & Lambon Ralph, M.A. Lichtheim 2: synthesizing aphasia and the neural basis of language in a neurocomputational model of the dual dorsal-ventral language pathways. Neuron 72, 385–396 (2011).

    Article  CAS  Google Scholar 

  28. Petersson, K.M., Forkstam, C. & Ingvar, M. Artificial syntactic violations activate Broca's region. Cogn. Sci. 28, 383–407 (2004).

    Google Scholar 

  29. Bornkessel, I., Zysset, S., Friederici, A.D., von Cramon, D.Y. & Schlesewsky, M. Who did what to whom? The neural basis of argument hierarchies during language comprehension. Neuroimage 26, 221–233 (2005).

    Article  Google Scholar 

  30. Gelfand, J.R. & Bookheimer, S.Y. Dissociating neural mechanisms of temporal sequencing and processing phonemes. Neuron 38, 831–842 (2003).

    Article  CAS  Google Scholar 

  31. Sridharan, D., Levitin, D.J., Chafe, C.H., Berger, J. & Menon, V. Neural dynamics of event segmentation in music: converging evidence for dissociable ventral and dorsal networks. Neuron 55, 521–532 (2007).

    Article  CAS  Google Scholar 

  32. Kilner, J.M., Neal, A., Weiskopf, N., Friston, K.J. & Frith, C.D. Evidence of mirror neurons in human inferior frontal gyrus. J. Neurosci. 29, 10153–10159 (2009).

    Article  CAS  Google Scholar 

  33. Bar, M., Aminoff, E., Mason, M. & Fenske, M. The units of thought. Hippocampus 17, 420–428 (2007).

    Article  Google Scholar 

  34. Ezzyat, Y. & Davachi, L. What constitutes an episode in episodic memory? Psychol. Sci. 22, 243–252 (2011).

    Article  Google Scholar 

  35. Koechlin, E., Corrado, G., Pietrini, P. & Grafman, J. Dissociating the role of the medial and lateral anterior prefrontal cortex in human planning. Proc. Natl. Acad. Sci. USA 97, 7651–7656 (2000).

    Article  CAS  Google Scholar 

  36. Wood, J.N., Knutson, K.M. & Grafman, J. Psychological structure and neural correlates of event knowledge. Cereb. Cortex 15, 1155–1161 (2005).

    Article  Google Scholar 

  37. Krueger, F. et al. The frontopolar cortex mediates event knowledge complexity: a parametric functional MRI study. Neuroreport 20, 1093–1097 (2009).

    PubMed  PubMed Central  Google Scholar 

  38. Addis, D.R., Wong, A.T. & Schacter, D.L. Remembering the past and imagining the future: common and distinct neural substrates during event construction and elaboration. Neuropsychologia 45, 1363–1377 (2007).

    Article  Google Scholar 

  39. Elman, J.L. Finding structure in time. Cogn. Sci. 14, 179–211 (1990).

    Article  Google Scholar 

  40. Cleeremans, A. & McClelland, J.L. Learning the structure of event sequences. J. Exp. Psychol. Gen. 120, 235–253 (1991).

    Article  CAS  Google Scholar 

  41. Landauer, T.K. & Dumais, S.T. A solution to Plato's problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychol. Rev. 104, 211–240 (1997).

    Article  Google Scholar 

  42. Griffiths, T.L., Steyvers, M. & Tenenbaum, J.B. Topics in semantic representation. Psychol. Rev. 114, 211–244 (2007).

    Article  Google Scholar 

  43. Howard, M.W., Shankar, K.H. & Jagadisan, U.K.K. Constructing semantic representations from a gradually changing representation of temporal context. Top. Cogn. Sci. 3, 48–73 (2011).

    Article  Google Scholar 

  44. Fiser, J. & Aslin, R.N. Statistical learning of higher-order temporal structure from visual shape sequences. J. Exp. Psychol. Learn. Mem. Cogn. 28, 458–467 (2002).

    Article  Google Scholar 

  45. Pothos, E.M. Theories of artificial grammar learning. Psychol. Bull. 133, 227–244 (2007).

    Article  Google Scholar 

  46. Remillard, G. Implicit learning of fifth- and sixth-order sequential probabilities. Mem. Cognit. 38, 905–915 (2010).

    Article  Google Scholar 

  47. Perruchet, P., Vinter, A., Pacteau, C. & Gallego, J. The formation of structurally relevant units in artificial grammar learning. Q. J. Exp. Psychol. A 55, 485–503 (2002).

    Article  Google Scholar 

  48. Perruchet, P. & Vinter, A. Parser: a model for word segmentation. J. Mem. Lang. 39, 246–263 (1998).

    Article  Google Scholar 

  49. Botvinick, M. & Plaut, D.C. Doing without schema hierarchies: a recurrent connectionist approach to normal and impaired routine sequential action. Psychol. Rev. 111, 395–429 (2004).

    Article  Google Scholar 

  50. Baird, J.A. & Baldwin, D.A. Making sense of human behavior: Action parsing and intentional inference. in Intentions and Intentionality: Foundations of Social Cognition (eds. B.F. Malle, L.J. Moses & D.A. Baldwin) 193–206 (MIT Press, Cambridge, Massachusetts, 2001).

  51. Pereira, F. & Botvinick, M. Information mapping with pattern classifiers: a comparative study. Neuroimage 56, 476–496 (2011).

    Article  Google Scholar 

Download references

Acknowledgements

We thank M. Arcaro, J. McGuire, K. Norman, F. Pereira and M. Todd for helpful discussions. This project was made possible through the support of a grant from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. This work was also supported by US National Science Foundation Graduate Research Fellowship DGE-0646086 to A.C.S., US National Institutes of Health grant R01-EY021755 to N.B.T.-B., and US National Science Foundation grant IIS-1207833 and a James S. McDonnell Foundation grant to M.M.B.

Author information

Authors and Affiliations

  1. Department of Psychology, Princeton University, Princeton, New Jersey, USA

    Anna C Schapiro, Natalia I Cordova, Nicholas B Turk-Browne & Matthew M Botvinick

  2. Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA

    Anna C Schapiro, Natalia I Cordova, Nicholas B Turk-Browne & Matthew M Botvinick

  3. Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USA

    Timothy T Rogers

Authors
  1. Anna C Schapiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Timothy T Rogers
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Natalia I Cordova
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nicholas B Turk-Browne
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matthew M Botvinick
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.C.S., T.T.R. and M.M.B. designed the experiments. A.C.S. and N.I.C. collected and analyzed the data. N.B.T.-B. provided guidance on data acquisition and analysis. A.C.S., T.T.R., M.M.B. and N.B.T.-B. wrote the paper. All of the authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Anna C Schapiro.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 and Supplementary Tables 1 and 2 (PDF 3341 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schapiro, A., Rogers, T., Cordova, N. et al. Neural representations of events arise from temporal community structure. Nat Neurosci 16, 486–492 (2013). https://doi.org/10.1038/nn.3331

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.3331

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing